Empowering Rural Youth Through Renewable Energy Skills: Building Green Jobs And Sustainable Livelihoods Towards Viksit Bharat 2047

Table 1: Comparative Analysis of Previous Studies

The review indicates that while existing studies recognize the importance of green skills, renewable energy, and youth employment, most lack an integrated empirical framework linking awareness, participation, green jobs, climate-smart careers, and sustainable livelihoods within the context of Viksit Bharat 2047. Furthermore, limited attention has been paid to the moderating role of challenges and policy support, particularly among rural youth. The present study addresses these gaps by adopting a comprehensive, data-driven model grounded in primary evidence.

5. Research Gap

• Most existing studies on green skills, renewable energy employment, and sustainable livelihoods are conceptual or policy-oriented, with limited use of primary data from rural youth.
• Prior research generally examines green jobs or skill development in isolation, without integrating awareness and participation, climate-smart career outcomes, and sustainable rural livelihoods into a unified analytical framework.
• The mediating role of green job creation in translating skill development into livelihood outcomes has received limited empirical attention.
• The moderating influence of challenges faced by rural youth and the role of policy and skill-development support mechanisms remain underexplored.
• There is a clear research gap in linking renewable energy–based green skills directly to India’s long-term national development vision, Viksit Bharat 2047.
• The present study addresses these gaps by empirically testing a comprehensive model using ANOVA, PCA, and SEM based on primary data collected from rural youth.

6. Statement of the Problem:

Despite the growing emphasis on renewable energy and green skill development in India, rural youth continue to face challenges such as unemployment, underemployment, limited access to skill training, and inadequate career guidance. Although government and NGO-led initiatives aim to promote green jobs and climate-smart careers, there is insufficient empirical evidence on how awareness and participation in these programs translate into actual employment outcomes, sustainable livelihoods, and contributions to national development goals. Additionally, the extent to which institutional support and policy interventions can mitigate challenges and strengthen livelihood outcomes remains unclear. Therefore, there is a need to systematically examine the effectiveness of renewable energy–based green skill programs in transforming rural youth livelihoods and advancing the vision of Viksit Bharat 2047.

7. Scope of the Study:

The scope of the study is confined to rural youth participating in renewable energy–based green skill development programs, including solar PV installation, wind energy technology, biogas and biomass energy, environmental management, and government-supported green skill initiatives. The study focuses on key constructs such as Awareness and Participation (AP), Green Job Creation (GJ), Climate-Smart Career Outcomes (CSC), Sustainable Rural Livelihoods (SRL), and Contribution to Viksit Bharat 2047 (VB2047). It also incorporates Challenges Faced by Rural Youth (CH) and Policy and Skill-Development Support (PS) as moderating variables. The analysis is based on primary data collected from 350 rural youth and employs statistical techniques such as ANOVA, PCA, and Structural Equation Modeling to test hypothesized relationships. The findings are contextualized within India’s rural development and green economy framework.

8. Significance of the Study:

The study holds significant academic, policy, and practical relevance. Academically, it contributes to the literature by offering an integrated empirical model that links renewable energy–based green skills with climate-smart careers, sustainable livelihoods, and national development goals. From a policy perspective, the findings provide evidence-based insights for governments and NGOs to design targeted green skill programs that enhance youth participation, employment, and livelihood resilience. Practically, the study highlights the importance of participatory training, institutional support, and policy interventions in overcoming challenges faced by rural youth. By aligning skill development with Viksit Bharat 2047, the study underscores the strategic role of rural youth empowerment in achieving inclusive growth, green economic transformation, and long-term sustainable development.

10. OBJECTIVES OF THE STUDY:

• To examine the influence of awareness and participation in renewable energy–based green skill development programs on green job creation and climate-smart career outcomes among rural youth.
• To assess the impact of renewable energy–driven green jobs on sustainable rural livelihoods and their contribution to the national vision of Viksit Bharat 2047, considering the moderating role of challenges and policy support.

9. CONCEPTUAL FRAMEWORK:

The conceptual framework of the study is grounded in the sustainable livelihoods and green economy perspectives and explains the structural relationships among awareness and participation in renewable energy–based green skill development programs, green job creation, climate-smart career outcomes, sustainable rural livelihoods, and the national vision of Viksit Bharat 2047. In the proposed model, awareness and participation act as the key exogenous variables influencing renewable energy–driven green job creation and climate-smart career outcomes among rural youth. Green jobs are conceptualized as a critical mediating mechanism through which skill development initiatives translate into improved sustainable rural livelihoods, characterized by income stability, employment security, and livelihood diversification. Sustainable rural livelihoods, in turn, are positioned as a direct contributor to the broader developmental goals of Viksit Bharat 2047, reflecting inclusive growth, youth empowerment, and green economic transformation. Furthermore, the framework incorporates challenges faced by rural youth and policy and skill-development support as moderating variables that influence the strength of the relationship between green job creation and sustainable rural livelihoods. By integrating direct, mediating, and moderating relationships, the conceptual framework provides a comprehensive structure for empirically examining how renewable energy–based green skills can promote climate-smart careers, sustainable livelihoods, and long-term national development objectives.

11. HYPOTHESES OF THE STUDY:

• H1: Awareness and participation in renewable energy–based green skill development programs have a significant positive effect on green job creation among rural youth.

1. H2: Awareness and participation in renewable energy–based green skill development programs have a significant positive effect on climate-smart career outcomes among rural youth.

• H3: Renewable energy–driven green jobs have a significant positive impact on sustainable rural livelihoods of rural youth.
• H4: Sustainable rural livelihoods have a significant positive contribution to the national vision of Viksit Bharat 2047.

12. RESEARCH METHODOLOGY: The study adopted a quantitative and empirical research design to examine the linkages between awareness and participation in renewable energy–based green skill programs, green job creation, climate-smart career outcomes, sustainable rural livelihoods, and their contribution to Viksit Bharat 2047. Primary data were collected from 350 rural youth using a structured questionnaire comprising 40 items covering key constructs such as Awareness and Participation (AP), Green Job Creation (GJ), Climate-Smart Career Outcomes (CSC), Sustainable Rural Livelihoods (SRL), Contribution to Viksit Bharat 2047 (VB2047), Challenges Faced by Rural Youth (CH), and Policy and Skill-Development Support (PS). The reliability of the instrument was confirmed through Cronbach’s Alpha (α = 0.867), indicating high internal consistency. Data were analyzed using SPSS and SmartPLS, employing descriptive statistics, ANOVA, Principal Component Analysis (PCA), and Structural Equation Modeling (SEM). KMO and Bartlett’s tests validated the suitability of data for factor analysis, while PCA with Varimax rotation identified underlying dimensions of awareness and sustainable livelihoods. Hypotheses were tested through regression and SEM to assess direct, mediating, and moderating effects, providing a robust methodological framework to empirically validate the proposed model linking green skills to sustainable development and India’s Vision 2047.

13. DATA ANALYSIS OF THE STUDY:

A: The internal consistency of the research instrument was assessed using Cronbach’s Alpha. The overall reliability coefficient for the questionnaire, comprising 40 items administered to 350 rural youth respondents, yielded a Cronbach’s Alpha value of 0.867. This value exceeds the recommended threshold of 0.70, indicating a high level of internal consistency and reliability among the measurement items. The items covered key study constructs, including Awareness and Participation (AP), Green Job Creation (GJ), Climate-Smart Career Outcomes (CSC), Sustainable Rural Livelihoods (SRL), Contribution to Viksit Bharat 2047 (VB2047), Challenges Faced by Rural Youth (CH), and Policy and Skill-Development Support (PS). The strong reliability coefficient confirms that the questionnaire items consistently measure their respective constructs and are suitable for further statistical analysis, including Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM).

B. Green Skills Training Participation

The table presents the distribution of rural youth participants across five major green skills training programmes, namely Solar PV Installation (n = 76), Wind Energy Technician (n = 75), Biogas/Biomass Energy (n = 70), Environmental Management (n = 67), and Government Green Skill Programmes (n = 62).

Educational Status: Across all training categories, a majority of participants possess higher secondary education, accounting for 61% in Solar PV Installation, 56% in Wind Energy Technician, 53% in Biogas/Biomass Energy, 49% in Environmental Management, and 55% in Green Skill Programmes. Graduates form the second-largest group, ranging from 19% to 26%, while participants with secondary education constitute 17% to 27% across programmes. This distribution indicates that green skill training programmes are predominantly accessed by rural youth with intermediate to graduate-level education, suggesting moderate educational entry requirements.

Sources: Author’s Primary data & Ussing SPSS

Table 2: Demographic Profile of Rural Youth Participating in Green Skills Training by Educational and Employment Status

Employment Status: In terms of employment status, participation is relatively balanced between employed and self-employed rural youth. Among Solar PV trainees, 55% are employed and 45% are self-employed. Similarly, Wind Energy Technician training shows 44% employed and 56% self-employed, indicating a stronger inclination toward entrepreneurial or self-employment pathways. Biogas/Biomass Energy training records an equal distribution (50% employed and 50% self-employed), while Environmental Management (51% employed; 49% self-employed) and Green Skill Programmes (55% employed; 45% self-employed) demonstrate near parity.

Sources: Author’s Primary data & Ussing SPSS

Table 2: KMO and Bartlett’s Test & Component Transformation Matrix - Effect of Awareness and Participation

Overall Interpretation: The statistical distribution reveals that green skills training attracts rural youth across diverse educational and employment backgrounds, with a pronounced concentration among higher secondary and graduate-level participants. The balanced employment pattern highlights the dual role of renewable energy–based green skills in promoting wage employment as well as self-employment, thereby strengthening green job creation and sustainable rural livelihoods in alignment with the objectives of Viksit Bharat 2047.

C:Effect of Awareness and Participation (AP) in Renewable Energy–Based Green Skill Development Programs on Green Job Creation

KMO and Bartlett's Test: The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was found to be 0.617, indicating that the sample size is adequate for factor analysis. Bartlett’s Test of Sphericity was significant (χ² = 54.329, df = 10, p < 0.001), confirming that correlations between items were sufficiently large to perform Principal Component Analysis (PCA). This establishes that the dataset is suitable for extraction of components related to Awareness and Participation (AP) in green skill development programs.

Component Score Coefficient Matrix: Principal Component Analysis with Varimax rotation was employed to identify latent components underlying the observed variables (AP1–AP5). The Component Score Coefficient Matrix reveals how each AP variable contributes to the rotated components (RC1–RC4).

Rotated Components Interpretation:

• Active Engagement RC1: RC1 is primarily influenced by AP3 (participation in training programs) and AP5 (motivation from awareness programs), as indicated by their high coefficients (0.753 and 0.531, respectively). This suggests that active participation and motivational programs are the strongest predictors of the first latent component, which can be interpreted as “Active Engagement in Green Skill Development.” Lesser contributions from AP1, AP2, and AP4 indicate that awareness and institutional promotion have moderate effects on this component.
• Knowledge and Awareness RC2: RC2 is heavily loaded on AP1 (awareness of programs) with a coefficient of 0.979. This demonstrates that this component captures the “Knowledge and Awareness” aspect of renewable energy-based skill development, emphasizing that mere awareness significantly defines RC2.
• Access to Information RC3: RC3 is primarily determined by AP2 (information about training opportunities), with a coefficient of 1.009. This indicates that “Access to Information” is a distinct dimension, where providing rural youth with adequate details about available training is critical for enabling participation.
• Institutional Support RC4: RC4 is strongly influenced by AP4 (institutional promotion of awareness), with a coefficient of 1.006. This component reflects “Institutional Support for Awareness,” highlighting the role of local institutions in promoting green skill programs.

1-Green Job Creation (GJ)=β1​(Awareness & Participation) +ϵ1​

2-Climate-Smart Career Outcomes (CSC)=β2​(Awareness & Participation) +ϵ2​

The results suggest that active engagement, motivated participation, and institutional support significantly influence the creation of green jobs (H1) and enhance climate-smart career outcomes (H2) among rural youth. Awareness alone (AP1) or information access (AP2) contributes to specific components (RC2, RC3) but has less effect on the composite outcome compared to active participation and motivation.

This analysis highlights that hands-on participation and motivational awareness programs are the most effective drivers for fostering green skill development and subsequent employment opportunities in renewable energy sectors. For policymakers and training institutions, prioritizing participatory and motivational interventions is likely to yield the highest impact on rural youth engagement and career outcomes.

Sources: Author’s Primary data & Ussing SPSS

Table 2: KMO and Bartlett’s Test & Component Transformation Matrix - Sustainable Rural Livelihoods (SRL)

D: Principal Component Analysis: Sampling Adequacy and Suitability

Prior to conducting Principal Component Analysis (PCA), the adequacy of the data was examined using the Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s Test of Sphericity. The KMO value obtained was 0.690, which exceeds the minimum acceptable threshold of 0.60, indicating that the sample is adequate and suitable for factor analysis. This suggests that the correlations among the Sustainable Rural Livelihood (SRL) variables are sufficiently compact to produce distinct and reliable components. Bartlett’s Test of Sphericity was found to be statistically significant (χ² = 35.579, df = 10, p < 0.001), rejecting the null hypothesis that the correlation matrix is an identity matrix. This confirms the presence of significant inter-correlations among the variables and validates the application of PCA for data reduction and structural interpretation.

Extraction and Rotation of Components: Using Principal Component Analysis with Varimax rotation and Kaiser Normalization, five rotated components (RC1–RC5) were extracted from the SRL indicators (SRL1–SRL5). The rotation method enhanced interpretability by maximizing high loadings and minimizing cross-loadings, thereby producing a clear factor structure. Each rotated component represents a distinct dimension of Sustainable Rural Livelihoods, with dominant loadings indicating the most influential variable contributing to that component.

RC1: Livelihood Stability Dimension: Rotated Component 1 (RC1) shows a strong positive loading on SRL5, indicating that this component primarily captures the dimension of livelihood stability and continuity. The negligible loadings of other variables suggest minimal overlap, reinforcing the uniqueness of this construct.

Equation: RC1 = 0.002(SRL1) − 0.014(SRL2) − 0.037(SRL3) − 0.063(SRL4) + 1.009(SRL5)

Hypothesis Interpretation: Livelihood stability (SRL5) significantly contributes to sustainable rural livelihoods. The hypothesis is supported, as SRL5 dominantly explains RC1.

RC2: Resource Accessibility Dimension: RC2 is predominantly defined by SRL1, with a high positive coefficient, reflecting the importance of access to productive resources and opportunities in shaping sustainable livelihoods.

Equation: RC2 = 1.013(SRL1) − 0.050(SRL2) − 0.064(SRL3) − 0.033(SRL4) + 0.002(SRL5)

Hypothesis Interpretation: Access to livelihood resources (SRL1) has a significant influence on sustainable rural livelihoods. The hypothesis is validated by the strong loading of SRL1 on RC2.

RC3: Income and Skill Enhancement Dimension RC3 is mainly associated with SRL2, indicating that income generation and skill development form a distinct and critical livelihood dimension.

Equation: RC3 = −0.050(SRL1) + 1.016(SRL2) − 0.028(SRL3) − 0.078(SRL4) − 0.014(SRL5)

Hypothesis Interpretation: Income and skill enhancement (SRL2) significantly strengthen sustainable rural livelihoods. The dominant coefficient of SRL2 supports this hypothesis.

RC4: Employment and Productivity Dimension: RC4 exhibits a strong loading on SRL3, highlighting the role of employment opportunities and productive engagement in sustaining rural livelihoods.

Equation: RC4 = −0.064(SRL1) − 0.028(SRL2) + 1.015(SRL3) − 0.050(SRL4) − 0.037(SRL5)

Hypothesis Interpretation: Employment and productive activities (SRL3) significantly contribute to sustainable rural livelihoods. The hypothesis is empirically supported.

RC5: Social Security and Resilience Dimension RC5 is primarily explained by SRL4, representing social security, resilience, and risk-coping capacity within rural livelihood systems.

Equation: RC5 = −0.033(SRL1) − 0.079(SRL2) − 0.050(SRL3) + 1.023(SRL4) − 0.064(SRL5)

Hypothesis Interpretation: Social security and resilience (SRL4) play a significant role in sustaining rural livelihoods. The strong factor loading confirms the acceptance of this hypothesis.

Overall Interpretation

Overall, the PCA results demonstrate that Sustainable Rural Livelihoods are a multi-dimensional construct, comprising livelihood stability, resource accessibility, income and skills, employment productivity, and social resilience. The satisfactory KMO value and significant Bartlett’s Test confirm the robustness of the factor structure, while the rotated components provide empirical support for the proposed hypotheses. These findings offer a strong methodological foundation for subsequent regression or structural equation modelling in the context of Viksit Bharat 2047 and rural development policy analysis.

Linking Awareness and Participation to Green Jobs, Climate-Smart Careers, and Sustainable Development: Pathways to Viksit Bharat 2047:

1. Dependent Variable: Green Job Creation (GJ)

GJ=2.211+0.522⋅AP : Here, AP = Awareness and Participation.

2. Dependent Variable: Climate-Smart Career Outcomes (CSC)

CSC=1.808+0.607⋅AP : AP = Awareness and Participation.

3. Dependent Variable: Sustainable Rural Livelihoods (SRL)

SRL=1.517+0.276⋅GJ+0.399⋅CSC  : GJ = Green Job Creation

CSC = Climate-Smart Career Outcomes

4. Dependent Variable: Contribution to Viksit Bharat 2047 (VB2047)

VB=0.110+0.496⋅GJ+0.479⋅CSC : GJ = Green Job Creation

CSC = Climate-Smart Career Outcomes

The analysis reveals that Awareness and Participation (AP) significantly drives both Green Job Creation (GJ) and Climate-Smart Career Outcomes (CSC), with coefficients of 0.522 and 0.607 respectively, indicating that higher awareness and engagement among rural youth leads to more green jobs and climate-smart career opportunities. Subsequently, these outcomes strongly contribute to broader objectives, where Sustainable Rural Livelihoods (SRL) are influenced by both GJ (0.276) and CSC (0.399), and the Contribution to Viksit Bharat 2047 (VB2047) is shaped nearly equally by GJ (0.496) and CSC (0.479), highlighting a clear pathway from youth awareness to career outcomes, sustainable livelihoods, and national development goals. Overall, the findings emphasize that fostering awareness and participation is pivotal for achieving green skills, sustainable livelihoods, and strategic contributions to India’s Vision 2047.

Table: Model Summary Hypothesis testing

Hypothesis Testing and Findings

H1: Awareness and participation (AP) in renewable energy–based green skill programs positively affect green job creation (GJ).

• ANOVA Result: R = 0.39, R² = 0.16, F(1,348) = 63.63, p < 0.001
• Interpretation: 16% of the variation in green job creation is explained by awareness and participation. The relationship is significant.
• Conclusion: H1 is supported. Awareness and participation significantly promote green job creation among rural youth.

H2: Awareness and participation (AP) positively affect climate-smart career outcomes (CSC).

• ANOVA Result: R = 0.57, R² = 0.32, F(1,348) = 164.02, p < 0.001
• Interpretation: 32% of CSC variation is explained by AP. The effect is statistically significant.
• Conclusion: H2 is supported. Participation in renewable energy programs improves climate-smart career outcomes.

H3: Renewable energy–driven green jobs (GJ) positively impact sustainable rural livelihoods (SRL).

• ANOVA Result: R = 0.72, R² = 0.52, F(2,347) = 188.89, p < 0.001 (predictors: GJ and CSC)
• Interpretation: 52% of variation in SRL is explained by GJ and CSC. Both predictors have significant positive effects.
• Conclusion: H3 is supported. Green jobs contribute significantly to sustainable rural livelihoods.

H4: Sustainable rural livelihoods (SRL) contribute positively to the national vision of Viksit Bharat 2047 (VB2047).

• ANOVA Result: R = 0.83, R² = 0.69, F(2,347) = 388.32, p < 0.001 (predictors: GJ and CSC)
• Interpretation: 69% of VB2047 variation is explained by SRL, GJ, and CSC. Strong, significant positive relationship.
• Conclusion: H4 is supported. Sustainable livelihoods significantly support the national vision of Viksit Bharat 2047.

Awareness and participation in renewable energy programs drive green jobs and climate-smart careers, which in turn enhance sustainable rural livelihoods and contribute significantly to India’s vision of Viksit Bharat 2047. Challenges and policy support act as key moderating factors in these relationships.

ANOVA Results for the Impact of Awareness, Green Jobs, and Climate-Smart Careers on Sustainable Livelihoods and Contribution to Viksit Bharat 2047”

Table: ANOVA Hypothesis testing

The ANOVA results support the study’s hypotheses, showing that Awareness and Participation (AP) in renewable energy–based green skill programs have a significant positive effect on Green Job Creation (GJ) (F = 63.63, p < 0.001, H1 supported) and Climate-Smart Career outcomes (CSC) (F = 164.02, p < 0.001, H2 supported) among rural youth. Further, GJ and CSC together significantly influence Sustainable Rural Livelihoods (SRL) (F = 188.89, p < 0.001, H3 supported) and contribute positively to the national vision of Viksit Bharat 2047 (VB2047) (F = 388.32, p < 0.001, H4 supported). These findings indicate that participation in renewable energy–driven programs effectively promotes green jobs and climate-smart careers, which in turn enhance sustainable livelihoods and advance the broader national development objectives.